Quasi-random sequences, also known as low-discrepancy or low-dispersion sequences, are sequences of points in an n-dimensional unit hypercube. These sequences have the property that points are spread more evenly throughout the cube than random point sequences, which result in regions where there are clusters of points and others that are sparsely populated. Based on the observation that program faults tend to lead to contiguous failure regions within a program's input domain, and that an even spread of random tests enhances the failure detection effectiveness for certain failure patterns, we examine the use of these sequences as a replacement for random sequences in automated testing.The limited number of quasi-random sequences available from the standard algorithms poses significant practical problems for use when testing real programs, and especially for evaluating its effectiveness. We examine the use of randomised quasi-random sequences, which are permuted in a nondeterministic fashion but still retain their low discrepancy properties, to overcome this problem, and show that testing using randomised quasi-random sequences is often significantly more effective than random testing.